Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## [1] "ASDAX"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## [1] "^TNX"
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## [1] "^IRX"
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "^GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## [1] "^RLG"
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "^DJI"
## [1] "^STOXX50E"
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.
## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "EXHOSLUSM495S"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## [1] "TMFGX"
## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"
## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 736680 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master
##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpOuWRlN\remotes817859a87e60\RamiKrispin-coronavirus-89f129d/DESCRIPTION'
## 
  
  
  
-  preparing 'coronavirus': (1.6s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (391ms)
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 
## Caught an warning!
## <simpleWarning: package 'coronavirus' is in use and will not be installed>
## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 20.73 compares to a historical mean value over the last decade of 18.62. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2022-06-16, is flat over the last year and flat over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 3.60% (last updated on 2022-05-01) which is near the 1-year average of 4.19% and rising with respect to the low in the last twelve months of 3.60%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 3.62% which is above the 1-year average of 4.45% and falling with respect to the peak, in the last twelve months, of 5.51%.

  • Jobless claims (ICSA data) year-over-year stands at -46.26% (last updated on 2022-06-11) which is in-line with the 1-year average of -65.32% and below the peak, in the last twelve months, of -44.86%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 1.22% (last updated on 2022-04-01). This is below the recent peak of 5.13%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at 1.64% (last updated on 2022-06-15). This is above the recent low of 1.14%. The trend is positive over the last year and flat over the last month.

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
9 PAYNSA All Employees: Total Nonfarm Payrolls (NSA)
12 INDPRO Industrial Production Index
14 RSALES Real Retail Sales (DISCONTINUED)
15 W875RX1 Real personal income excluding current transfer receipts
17 PCOPPUSDM Global price of Copper
55 HNFSUSNSA New One Family Houses for Sale in the United States (Monthly, NSA)
56 BUSLOANS Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
57 TOTCI Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
58 BUSLOANSNSA Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
59 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
60 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
61 RELACBW027NBOG Real Estate Loans, All Commercial Banks (Weekly, NSA)
62 RELACBW027SBOG Real Estate Loans, All Commercial Banks (Weekly, SA)
63 RREACBM027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
64 RREACBM027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
65 RREACBW027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
66 RREACBW027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
67 MORTGAGE30US 30-Year Fixed Rate Mortgage Average in the United States
68 CONSUMERNSA Consumer Loans, All Commercial Banks
69 TOTLLNSA Loans and Leases in Bank Credit, All Commercial Banks
72 TOTCINSA Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
73 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
74 ASTLL All sectors; total loans; liability, Level (NSA)
75 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
76 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
77 ASTMA All sectors; total mortgages; asset, Level (NSA)
78 ASHMA All sectors; home mortgages; asset, Level (NSA)
79 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
80 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
81 ASFMA All sectors; farm mortgages; asset, Level (NSA)
82 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
83 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
84 FBLL Domestic financial sectors loans; liability, Level (NSA)
85 NCBDBIQ027S Nonfinancial corporate business; debt securities; liability, Level
92 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
97 NEWORDER Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
109 GDP Gross Domestic Product
110 FNDEFX Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
114 GDPDEF Gross Domestic Product: Implicit Price Deflator
116 WLRRAL Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
117 FEDFUNDS Effective Federal Funds Rate
118 GPDI Gross Private Domestic Investment
120 MZMV Velocity of MZM Money Stock
121 M1 M1 Money Stock
122 M2 M2 Money Stock
124 IPMAN Industrial Production: Manufacturing (NAICS)
126 GS5 5-Year Treasury Constant Maturity Rate
131 GFDEBTN Federal Debt: Total Public Debt
134 MSPUS Median Sales Price of Houses Sold for the United States (NSA)
136 DGORDER Manufacturers’ New Orders: Durable Goods (SA)
137 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
138 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
139 FYFSD Federal Surplus or Deficit
140 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
145 OUTMS Manufacturing Sector: Real Output
146 MANEMP All Employees: Manufacturing
149 AAA Moody’s Seasoned Aaa Corporate Bond Yield
152 SOFR99 Secured Overnight Financing Rate: 99th Percentile
156 OBFR Overnight Bank Funding Rate
157 OBFR99 Overnight Bank Funding Rate: 99th Percentile
158 OBFR75 Overnight Bank Funding Rate: 75th Percentile
162 IOER Interest Rate on Excess Reserves
164 EXCSRESNW Excess Reserves of Depository Institutions
165 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
166 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
167 CEU0600000007 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
168 CURRENCY Currency Component of M1 (Seasonally Adjusted)
169 WCURRNS Currency Component of M1
172 PPIACO Producer Price Index for All Commodities
173 PCUOMFGOMFG Producer Price Index by Industry: Total Manufacturing Industries
174 POPTHM Population (U.S.)
175 POPTHM Population (U.S.)
181 FRGSHPUSM649NCIS Cass Freight Index: Shipments
183 TERMCBPER24NS Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
184 A065RC1A027NBEA Personal income (NSA)
185 PI Personal income (SA)
186 PCE Personal Consumption Expenditures (SA)
187 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
227 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
228 MULTPLSP500DIVYIELDMONTH S&P 500 Dividend Yield by Month
230 CHRISCMEHG1 Copper Futures, Continuous Contract #1 (HG1) (Front Month)
231 WWDIWLDISAIRGOODMTK1 Air transport, freight
234 PETA123600001M U.S. Regular Gasoline Retail Sales by Refiners, Monthly
235 PETA143B00001M U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
237 TOTALOGNRPUSM Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
238 TOTALPANRPUSM Crude Oil Rotary Rigs in Operation, Monthly
239 TOTALNGNRPUSM Natural Gas Rotary Rigs in Operation, Monthly
240 BKRTotal Total Rig Count
241 BKRGas Gas Rig Count
242 BKROil Oil Rig Count
243 FARMINCOME Net Farm Income
244 OPEARNINGSPERSHARE Operating Earnings per Share
245 AREARNINGSPERSHARE As-Reported Earnings per Share
246 CASHDIVIDENDSPERSHR Cash Dividends per Share
247 SALESPERSHR Sales per Share
248 BOOKVALPERSHR Book value per Share
249 CAPEXPERSHR Cap ex per Share
250 PRICE Price
251 OPEARNINGSTTM TTM Operating Earnings
252 AREARNINGSTTM TTM Reported Earnings
253 FINRAMarginDebt Margin Debt
254 FINRAFreeCreditMargin Free Credit Balances in Customers’ Securities Margin Accounts
255 OCCEquityVolume Equity Options Volume
256 OCCNonEquityVolume Non-Equity Options Volume
260 BUSLOANS.by.GDP Business Loans Normalized by GDP
263 BUSLOANSNSA.by.GDP Business Loans Normalized by GDP
264 TOTCI.by.GDP Business Loans (Weekly, SA) Normalized by GDP
265 TOTCINSA.by.GDP Business Loans (Weekly, NSA) Normalized by GDP
268 W875RX1.by.GDP Real Personal Income Normalized by GDP
270 PI.by.GDP Personal Income (SA) Normalized by GDP
271 A053RC1Q027SBEA.by.GDP National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
273 CONSUMERNSA.by.GDP Consumer Loans Not Seasonally Adjusted divided by GDP
274 RREACBM027NBOG.by.GDP Residental Real Estate Loans (Monthly, NSA) divided by GDP
275 RREACBM027SBOG.by.GDP Residental Real Estate Loans (Monthly, SA) divided by GDP
276 RREACBW027SBOG.by.GDP Residental Real Estate Loans (Weekly, SA) divided by GDP
277 RREACBW027NBOG.by.GDP Residental Real Estate Loans (Weekly, NSA) divided by GDP
279 DGORDER.by.GDP Durable Goods (Monthly, NSA) divided by GDP
280 ASHMA.by.GDP Home Mortgages (Quarterly, NSA) divided by GDP
281 ASHMA.INTEREST Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
282 ASHMA.INTEREST.by.GDP Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
283 CONSUMERNSA.INTEREST Consumer Loans (Not Seasonally Adjusted) Interest Burdens
284 CONSUMERNSA.INTEREST.by.GDP Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
285 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
286 TOTLNNSA.by.GDP Total Loans Not Seasonally Adjusted divided by GDP
291 WLRRAL.by.GDP Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
293 EXPCH.minus.IMPCH U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
295 SRPSABSNNCB.by.GDP Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
296 ASTLL.by.GDP All sectors; total loans; liability, Level (NSA) Divided by GDP
299 ASFMA.INTEREST Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
300 ASFMA.INTEREST.by.GDP Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
313 NPPTTLBYPOPTHM ADP Private Employment / Population
314 U6toU3 U6RATE minums UNRATE
324 GSG.Close.by.GSPC.Close GSCI Commodity-Indexed Trust, Normalized by S&P 500
333 HNFSUSNSA.minus.HSN1FNSA Houses for sale - houses sold
335 MSPUS.times.HNFSUSNSA New privately owned 1-family units for sale times median price
341 CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
343 CPIAUCSL_SmoothDer Derivative of Smoothed Consumer Price Index for All Urban Consumers: All Items
344 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
345 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
346 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
347 USREC_YoY NBER based Recession Indicators Year over Year
348 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
349 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
350 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
351 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
352 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
353 USREC_Log Log of NBER based Recession Indicators
354 USREC_mva200 NBER based Recession Indicators 200 Day MA
355 USREC_mva050 NBER based Recession Indicators 50 Day MA
356 UNRATE_YoY Civilian Unemployment Rate U-3 Year over Year
361 UNRATE_SmoothDer Derivative of Smoothed Civilian Unemployment Rate U-3
371 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
372 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
373 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
374 CCSA_YoY Continued Claims (Insured Unemployment) Year over Year
379 CCSA_SmoothDer Derivative of Smoothed Continued Claims (Insured Unemployment)
398 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
399 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
400 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
401 U6RATE_YoY Total unemployed + margin + part-time U-6 Year over Year
402 U6RATE_YoY4 Total unemployed + margin + part-time U-6 4 Year over 4 Year
403 U6RATE_YoY5 Total unemployed + margin + part-time U-6 5 Year over 5 Year
406 U6RATE_SmoothDer Derivative of Smoothed Total unemployed + margin + part-time U-6
413 PAYNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Total Nonfarm Payrolls (NSA)
415 PAYNSA_SmoothDer Derivative of Smoothed All Employees: Total Nonfarm Payrolls (NSA)
416 PAYNSA_Log Log of All Employees: Total Nonfarm Payrolls (NSA)
417 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
418 PAYNSA_mva050 All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
422 TABSHNO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; total assets, Level
431 HNONWPDPI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Household Net Worth, percent Dispsable Income
433 HNONWPDPI_SmoothDer Derivative of Smoothed Household Net Worth, percent Dispsable Income
442 INDPRO_SmoothDer Derivative of Smoothed Industrial Production Index
443 INDPRO_Log Log of Industrial Production Index
444 INDPRO_mva200 Industrial Production Index 200 Day MA
445 INDPRO_mva050 Industrial Production Index 50 Day MA
451 RRSFS_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales
453 RRSFS_mva200 Real Retail and Food Services Sales 200 Day MA
455 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
456 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
457 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
461 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
462 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
463 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
467 W875RX1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real personal income excluding current transfer receipts
470 W875RX1_Log Log of Real personal income excluding current transfer receipts
471 W875RX1_mva200 Real personal income excluding current transfer receipts 200 Day MA
472 W875RX1_mva050 Real personal income excluding current transfer receipts 50 Day MA
483 PCOPPUSDM_YoY4 Global price of Copper 4 Year over 4 Year
487 PCOPPUSDM_SmoothDer Derivative of Smoothed Global price of Copper
488 PCOPPUSDM_Log Log of Global price of Copper
534 NOBL.Volume_mva200 200 Day MA
588 SCHD.Volume_mva200 200 Day MA
658 HPI.Open_SmoothDer Derivative of Smoothed
667 HPI.High_SmoothDer Derivative of Smoothed
676 HPI.Low_SmoothDer Derivative of Smoothed
685 HPI.Close_SmoothDer Derivative of Smoothed
696 HPI.Volume_mva200 200 Day MA
703 HPI.Adjusted_SmoothDer Derivative of Smoothed
743 GSFTX.Volume_YoY Year over Year
744 GSFTX.Volume_YoY4 4 Year over 4 Year
745 GSFTX.Volume_YoY5 5 Year over 5 Year
746 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
747 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
748 GSFTX.Volume_SmoothDer Derivative of Smoothed
749 GSFTX.Volume_Log Log of
750 GSFTX.Volume_mva200 200 Day MA
751 GSFTX.Volume_mva050 50 Day MA
764 LFMIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
766 LFMIX.Open_SmoothDer Derivative of Smoothed
769 LFMIX.Open_mva050 50 Day MA
773 LFMIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
775 LFMIX.High_SmoothDer Derivative of Smoothed
778 LFMIX.High_mva050 50 Day MA
782 LFMIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
784 LFMIX.Low_SmoothDer Derivative of Smoothed
787 LFMIX.Low_mva050 50 Day MA
791 LFMIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
793 LFMIX.Close_SmoothDer Derivative of Smoothed
796 LFMIX.Close_mva050 50 Day MA
797 LFMIX.Volume_YoY Year over Year
798 LFMIX.Volume_YoY4 4 Year over 4 Year
799 LFMIX.Volume_YoY5 5 Year over 5 Year
800 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
801 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
802 LFMIX.Volume_SmoothDer Derivative of Smoothed
803 LFMIX.Volume_Log Log of
804 LFMIX.Volume_mva200 200 Day MA
805 LFMIX.Volume_mva050 50 Day MA
809 LFMIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
811 LFMIX.Adjusted_SmoothDer Derivative of Smoothed
813 LFMIX.Adjusted_mva200 200 Day MA
814 LFMIX.Adjusted_mva050 50 Day MA
818 LFMCX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
820 LFMCX.Open_SmoothDer Derivative of Smoothed
823 LFMCX.Open_mva050 50 Day MA
827 LFMCX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
829 LFMCX.High_SmoothDer Derivative of Smoothed
832 LFMCX.High_mva050 50 Day MA
836 LFMCX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
838 LFMCX.Low_SmoothDer Derivative of Smoothed
841 LFMCX.Low_mva050 50 Day MA
845 LFMCX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
847 LFMCX.Close_SmoothDer Derivative of Smoothed
850 LFMCX.Close_mva050 50 Day MA
851 LFMCX.Volume_YoY Year over Year
852 LFMCX.Volume_YoY4 4 Year over 4 Year
853 LFMCX.Volume_YoY5 5 Year over 5 Year
854 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
855 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
856 LFMCX.Volume_SmoothDer Derivative of Smoothed
857 LFMCX.Volume_Log Log of
858 LFMCX.Volume_mva200 200 Day MA
859 LFMCX.Volume_mva050 50 Day MA
863 LFMCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
865 LFMCX.Adjusted_SmoothDer Derivative of Smoothed
867 LFMCX.Adjusted_mva200 200 Day MA
868 LFMCX.Adjusted_mva050 50 Day MA
872 LFMAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
874 LFMAX.Open_SmoothDer Derivative of Smoothed
877 LFMAX.Open_mva050 50 Day MA
881 LFMAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
883 LFMAX.High_SmoothDer Derivative of Smoothed
886 LFMAX.High_mva050 50 Day MA
890 LFMAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
892 LFMAX.Low_SmoothDer Derivative of Smoothed
895 LFMAX.Low_mva050 50 Day MA
899 LFMAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
901 LFMAX.Close_SmoothDer Derivative of Smoothed
904 LFMAX.Close_mva050 50 Day MA
905 LFMAX.Volume_YoY Year over Year
906 LFMAX.Volume_YoY4 4 Year over 4 Year
907 LFMAX.Volume_YoY5 5 Year over 5 Year
908 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
909 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
910 LFMAX.Volume_SmoothDer Derivative of Smoothed
911 LFMAX.Volume_Log Log of
912 LFMAX.Volume_mva200 200 Day MA
913 LFMAX.Volume_mva050 50 Day MA
917 LFMAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
919 LFMAX.Adjusted_SmoothDer Derivative of Smoothed
921 LFMAX.Adjusted_mva200 200 Day MA
922 LFMAX.Adjusted_mva050 50 Day MA
926 LCSIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
928 LCSIX.Open_SmoothDer Derivative of Smoothed
935 LCSIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
937 LCSIX.High_SmoothDer Derivative of Smoothed
944 LCSIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
946 LCSIX.Low_SmoothDer Derivative of Smoothed
953 LCSIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
955 LCSIX.Close_SmoothDer Derivative of Smoothed
959 LCSIX.Volume_YoY Year over Year
960 LCSIX.Volume_YoY4 4 Year over 4 Year
961 LCSIX.Volume_YoY5 5 Year over 5 Year
962 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
963 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
964 LCSIX.Volume_SmoothDer Derivative of Smoothed
965 LCSIX.Volume_Log Log of
966 LCSIX.Volume_mva200 200 Day MA
967 LCSIX.Volume_mva050 50 Day MA
971 LCSIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
975 LCSIX.Adjusted_mva200 200 Day MA
1018 BSV.Volume_SmoothDer Derivative of Smoothed
1020 BSV.Volume_mva200 200 Day MA
1067 VBIRX.Volume_YoY Year over Year
1068 VBIRX.Volume_YoY4 4 Year over 4 Year
1069 VBIRX.Volume_YoY5 5 Year over 5 Year
1070 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1071 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1072 VBIRX.Volume_SmoothDer Derivative of Smoothed
1073 VBIRX.Volume_Log Log of
1074 VBIRX.Volume_mva200 200 Day MA
1075 VBIRX.Volume_mva050 50 Day MA
1175 VFSUX.Volume_YoY Year over Year
1176 VFSUX.Volume_YoY4 4 Year over 4 Year
1177 VFSUX.Volume_YoY5 5 Year over 5 Year
1178 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1179 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1180 VFSUX.Volume_SmoothDer Derivative of Smoothed
1181 VFSUX.Volume_Log Log of
1182 VFSUX.Volume_mva200 200 Day MA
1183 VFSUX.Volume_mva050 50 Day MA
1229 LTUIX.Volume_YoY Year over Year
1230 LTUIX.Volume_YoY4 4 Year over 4 Year
1231 LTUIX.Volume_YoY5 5 Year over 5 Year
1232 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1233 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1234 LTUIX.Volume_SmoothDer Derivative of Smoothed
1235 LTUIX.Volume_Log Log of
1236 LTUIX.Volume_mva200 200 Day MA
1237 LTUIX.Volume_mva050 50 Day MA
1283 PTTPX.Volume_YoY Year over Year
1284 PTTPX.Volume_YoY4 4 Year over 4 Year
1285 PTTPX.Volume_YoY5 5 Year over 5 Year
1286 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1287 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1288 PTTPX.Volume_SmoothDer Derivative of Smoothed
1289 PTTPX.Volume_Log Log of
1290 PTTPX.Volume_mva200 200 Day MA
1291 PTTPX.Volume_mva050 50 Day MA
1337 NERYX.Volume_YoY Year over Year
1338 NERYX.Volume_YoY4 4 Year over 4 Year
1339 NERYX.Volume_YoY5 5 Year over 5 Year
1340 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1341 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1342 NERYX.Volume_SmoothDer Derivative of Smoothed
1343 NERYX.Volume_Log Log of
1344 NERYX.Volume_mva200 200 Day MA
1345 NERYX.Volume_mva050 50 Day MA
1391 STIGX.Volume_YoY Year over Year
1392 STIGX.Volume_YoY4 4 Year over 4 Year
1393 STIGX.Volume_YoY5 5 Year over 5 Year
1394 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1395 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1396 STIGX.Volume_SmoothDer Derivative of Smoothed
1397 STIGX.Volume_Log Log of
1398 STIGX.Volume_mva200 200 Day MA
1399 STIGX.Volume_mva050 50 Day MA
1445 HLGAX.Volume_YoY Year over Year
1446 HLGAX.Volume_YoY4 4 Year over 4 Year
1447 HLGAX.Volume_YoY5 5 Year over 5 Year
1448 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1449 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1450 HLGAX.Volume_SmoothDer Derivative of Smoothed
1451 HLGAX.Volume_Log Log of
1452 HLGAX.Volume_mva200 200 Day MA
1453 HLGAX.Volume_mva050 50 Day MA
1499 FTRGX.Volume_YoY Year over Year
1500 FTRGX.Volume_YoY4 4 Year over 4 Year
1501 FTRGX.Volume_YoY5 5 Year over 5 Year
1502 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1503 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1504 FTRGX.Volume_SmoothDer Derivative of Smoothed
1505 FTRGX.Volume_Log Log of
1506 FTRGX.Volume_mva200 200 Day MA
1507 FTRGX.Volume_mva050 50 Day MA
1553 THIIX.Volume_YoY Year over Year
1554 THIIX.Volume_YoY4 4 Year over 4 Year
1555 THIIX.Volume_YoY5 5 Year over 5 Year
1556 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1557 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1558 THIIX.Volume_SmoothDer Derivative of Smoothed
1559 THIIX.Volume_Log Log of
1560 THIIX.Volume_mva200 200 Day MA
1561 THIIX.Volume_mva050 50 Day MA
1607 PTTRX.Volume_YoY Year over Year
1608 PTTRX.Volume_YoY4 4 Year over 4 Year
1609 PTTRX.Volume_YoY5 5 Year over 5 Year
1610 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1611 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1612 PTTRX.Volume_SmoothDer Derivative of Smoothed
1613 PTTRX.Volume_Log Log of
1614 PTTRX.Volume_mva200 200 Day MA
1615 PTTRX.Volume_mva050 50 Day MA
1661 BFIGX.Volume_YoY Year over Year
1662 BFIGX.Volume_YoY4 4 Year over 4 Year
1663 BFIGX.Volume_YoY5 5 Year over 5 Year
1664 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1665 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1666 BFIGX.Volume_SmoothDer Derivative of Smoothed
1667 BFIGX.Volume_Log Log of
1668 BFIGX.Volume_mva200 200 Day MA
1669 BFIGX.Volume_mva050 50 Day MA
1769 EIFAX.Volume_YoY Year over Year
1770 EIFAX.Volume_YoY4 4 Year over 4 Year
1771 EIFAX.Volume_YoY5 5 Year over 5 Year
1772 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1773 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1774 EIFAX.Volume_SmoothDer Derivative of Smoothed
1775 EIFAX.Volume_Log Log of
1776 EIFAX.Volume_mva200 200 Day MA
1777 EIFAX.Volume_mva050 50 Day MA
1823 ASDAX.Volume_YoY Year over Year
1824 ASDAX.Volume_YoY4 4 Year over 4 Year
1825 ASDAX.Volume_YoY5 5 Year over 5 Year
1826 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1827 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1828 ASDAX.Volume_SmoothDer Derivative of Smoothed
1829 ASDAX.Volume_Log Log of
1830 ASDAX.Volume_mva200 200 Day MA
1831 ASDAX.Volume_mva050 50 Day MA
1877 TRBUX.Volume_YoY Year over Year
1878 TRBUX.Volume_YoY4 4 Year over 4 Year
1879 TRBUX.Volume_YoY5 5 Year over 5 Year
1880 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1881 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1882 TRBUX.Volume_SmoothDer Derivative of Smoothed
1883 TRBUX.Volume_Log Log of
1884 TRBUX.Volume_mva200 200 Day MA
1885 TRBUX.Volume_mva050 50 Day MA
1931 PRVIX.Volume_YoY Year over Year
1932 PRVIX.Volume_YoY4 4 Year over 4 Year
1933 PRVIX.Volume_YoY5 5 Year over 5 Year
1934 PRVIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1935 PRVIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1936 PRVIX.Volume_SmoothDer Derivative of Smoothed
1937 PRVIX.Volume_Log Log of
1938 PRVIX.Volume_mva200 200 Day MA
1939 PRVIX.Volume_mva050 50 Day MA
1985 PRWCX.Volume_YoY Year over Year
1986 PRWCX.Volume_YoY4 4 Year over 4 Year
1987 PRWCX.Volume_YoY5 5 Year over 5 Year
1988 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1989 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1990 PRWCX.Volume_SmoothDer Derivative of Smoothed
1991 PRWCX.Volume_Log Log of
1992 PRWCX.Volume_mva200 200 Day MA
1993 PRWCX.Volume_mva050 50 Day MA
2039 ADOZX.Volume_YoY Year over Year
2040 ADOZX.Volume_YoY4 4 Year over 4 Year
2041 ADOZX.Volume_YoY5 5 Year over 5 Year
2042 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2043 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2044 ADOZX.Volume_SmoothDer Derivative of Smoothed
2045 ADOZX.Volume_Log Log of
2046 ADOZX.Volume_mva200 200 Day MA
2047 ADOZX.Volume_mva050 50 Day MA
2062 MERFX.Open_SmoothDer Derivative of Smoothed
2071 MERFX.High_SmoothDer Derivative of Smoothed
2080 MERFX.Low_SmoothDer Derivative of Smoothed
2089 MERFX.Close_SmoothDer Derivative of Smoothed
2093 MERFX.Volume_YoY Year over Year
2094 MERFX.Volume_YoY4 4 Year over 4 Year
2095 MERFX.Volume_YoY5 5 Year over 5 Year
2096 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2097 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2098 MERFX.Volume_SmoothDer Derivative of Smoothed
2099 MERFX.Volume_Log Log of
2100 MERFX.Volume_mva200 200 Day MA
2101 MERFX.Volume_mva050 50 Day MA
2107 MERFX.Adjusted_SmoothDer Derivative of Smoothed
2147 CMNIX.Volume_YoY Year over Year
2148 CMNIX.Volume_YoY4 4 Year over 4 Year
2149 CMNIX.Volume_YoY5 5 Year over 5 Year
2150 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2151 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2152 CMNIX.Volume_SmoothDer Derivative of Smoothed
2153 CMNIX.Volume_Log Log of
2154 CMNIX.Volume_mva200 200 Day MA
2155 CMNIX.Volume_mva050 50 Day MA
2201 CIHEX.Volume_YoY Year over Year
2202 CIHEX.Volume_YoY4 4 Year over 4 Year
2203 CIHEX.Volume_YoY5 5 Year over 5 Year
2204 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2205 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2206 CIHEX.Volume_SmoothDer Derivative of Smoothed
2207 CIHEX.Volume_Log Log of
2208 CIHEX.Volume_mva200 200 Day MA
2209 CIHEX.Volume_mva050 50 Day MA
2240 IMPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2242 IMPMX_SmoothDer Derivative of Smoothed U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2244 IMPMX_mva200 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2249 EXPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2251 EXPMX_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2253 EXPMX_mva200 U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 200 Day MA
2267 HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses for Sale in the United States (Monthly, NSA)
2269 HNFSUSNSA_SmoothDer Derivative of Smoothed New One Family Houses for Sale in the United States (Monthly, NSA)
2270 HNFSUSNSA_Log Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2271 HNFSUSNSA_mva200 New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2272 HNFSUSNSA_mva050 New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2273 BUSLOANS_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) Year over Year
2276 BUSLOANS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2278 BUSLOANS_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2279 BUSLOANS_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2280 BUSLOANS_mva200 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2281 BUSLOANS_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2282 TOTCI_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) Year over Year
2285 TOTCI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2287 TOTCI_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2288 TOTCI_Log Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2289 TOTCI_mva200 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2290 TOTCI_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2291 BUSLOANSNSA_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) Year over Year
2293 BUSLOANSNSA_YoY5 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 5 Year over 5 Year
2294 BUSLOANSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2296 BUSLOANSNSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2297 BUSLOANSNSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2298 BUSLOANSNSA_mva200 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2299 BUSLOANSNSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2303 REALLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, NSA)
2306 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2307 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2308 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2312 REALLN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2314 REALLN_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, SA)
2315 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2316 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2317 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2321 RELACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2323 RELACBW027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, NSA)
2324 RELACBW027NBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, NSA)
2325 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2326 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2330 RELACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2332 RELACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2333 RELACBW027SBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2334 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2335 RELACBW027SBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2339 RREACBM027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2342 RREACBM027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2343 RREACBM027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2344 RREACBM027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2348 RREACBM027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2350 RREACBM027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2351 RREACBM027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2352 RREACBM027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2353 RREACBM027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2357 RREACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2359 RREACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2360 RREACBW027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2361 RREACBW027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2362 RREACBW027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2365 RREACBW027NBOG_YoY5 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 5 Year over 5 Year
2366 RREACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2369 RREACBW027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2370 RREACBW027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2371 RREACBW027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2372 MORTGAGE30US_YoY 30-Year Fixed Rate Mortgage Average in the United States Year over Year
2373 MORTGAGE30US_YoY4 30-Year Fixed Rate Mortgage Average in the United States 4 Year over 4 Year
2374 MORTGAGE30US_YoY5 30-Year Fixed Rate Mortgage Average in the United States 5 Year over 5 Year
2375 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2376 MORTGAGE30US_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 30-Year Fixed Rate Mortgage Average in the United States
2377 MORTGAGE30US_SmoothDer Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2378 MORTGAGE30US_Log Log of 30-Year Fixed Rate Mortgage Average in the United States
2379 MORTGAGE30US_mva200 30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2380 MORTGAGE30US_mva050 30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2384 CONSUMERNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans, All Commercial Banks
2387 CONSUMERNSA_Log Log of Consumer Loans, All Commercial Banks
2388 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2389 CONSUMERNSA_mva050 Consumer Loans, All Commercial Banks 50 Day MA
2390 TOTLLNSA_YoY Loans and Leases in Bank Credit, All Commercial Banks Year over Year
2393 TOTLLNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2395 TOTLLNSA_SmoothDer Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2396 TOTLLNSA_Log Log of Loans and Leases in Bank Credit, All Commercial Banks
2397 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2398 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2406 DPSACBW027SBOG_mva200 Deposits, All Commercial Banks 200 Day MA
2411 DRCLACBS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2417 TOTCINSA_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) Year over Year
2420 TOTCINSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2422 TOTCINSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2423 TOTCINSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2424 TOTCINSA_mva200 Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2425 TOTCINSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2427 SRPSABSNNCB_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2428 SRPSABSNNCB_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 5 Year over 5 Year
2432 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2433 SRPSABSNNCB_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2434 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2441 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2442 ASTLL_mva200 All sectors; total loans; liability, Level (NSA) 200 Day MA
2443 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2444 FBDILNECA_YoY Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) Year over Year
2450 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2451 FBDILNECA_mva200 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2452 FBDILNECA_mva050 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2459 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2460 ASOLAL_mva200 All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2461 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2468 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2469 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2470 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2477 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2478 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2479 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2486 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2487 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2488 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2495 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2496 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2497 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2504 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2505 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2506 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2513 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2514 CCLBSHNO_mva200 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2515 CCLBSHNO_mva050 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2522 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2523 FBDSILQ027S_mva200 Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2524 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2526 FBLL_YoY4 Domestic financial sectors loans; liability, Level (NSA) 4 Year over 4 Year
2531 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2532 FBLL_mva200 Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2533 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2540 NCBDBIQ027S_Log Log of Nonfinancial corporate business; debt securities; liability, Level
2541 NCBDBIQ027S_mva200 Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2542 NCBDBIQ027S_mva050 Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2546 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2548 DGS10_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2550 DGS10_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2551 DGS10_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2552 TNX.Open_YoY Year over Year
2553 TNX.Open_YoY4 4 Year over 4 Year
2554 TNX.Open_YoY5 5 Year over 5 Year
2555 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2556 TNX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2557 TNX.Open_SmoothDer Derivative of Smoothed
2558 TNX.Open_Log Log of
2559 TNX.Open_mva200 200 Day MA
2560 TNX.Open_mva050 50 Day MA
2564 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2565 TNX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2566 TNX.High_SmoothDer Derivative of Smoothed
2568 TNX.High_mva200 200 Day MA
2569 TNX.High_mva050 50 Day MA
2573 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2574 TNX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2575 TNX.Low_SmoothDer Derivative of Smoothed
2577 TNX.Low_mva200 200 Day MA
2578 TNX.Low_mva050 50 Day MA
2582 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2584 TNX.Close_SmoothDer Derivative of Smoothed
2586 TNX.Close_mva200 200 Day MA
2587 TNX.Close_mva050 50 Day MA
2588 TNX.Volume_YoY Year over Year
2589 TNX.Volume_YoY4 4 Year over 4 Year
2590 TNX.Volume_YoY5 5 Year over 5 Year
2591 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2592 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2593 TNX.Volume_SmoothDer Derivative of Smoothed
2594 TNX.Volume_Log Log of
2595 TNX.Volume_mva200 200 Day MA
2596 TNX.Volume_mva050 50 Day MA
2600 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2602 TNX.Adjusted_SmoothDer Derivative of Smoothed
2604 TNX.Adjusted_mva200 200 Day MA
2605 TNX.Adjusted_mva050 50 Day MA
2609 CLF.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2611 CLF.Open_SmoothDer Derivative of Smoothed
2612 CLF.Open_Log Log of
2613 CLF.Open_mva200 200 Day MA
2614 CLF.Open_mva050 50 Day MA
2618 CLF.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2620 CLF.High_SmoothDer Derivative of Smoothed
2622 CLF.High_mva200 200 Day MA
2623 CLF.High_mva050 50 Day MA
2627 CLF.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2629 CLF.Low_SmoothDer Derivative of Smoothed
2630 CLF.Low_Log Log of
2631 CLF.Low_mva200 200 Day MA
2632 CLF.Low_mva050 50 Day MA
2636 CLF.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2638 CLF.Close_SmoothDer Derivative of Smoothed
2639 CLF.Close_Log Log of
2640 CLF.Close_mva200 200 Day MA
2641 CLF.Close_mva050 50 Day MA
2648 CLF.Volume_Log Log of
2654 CLF.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2656 CLF.Adjusted_SmoothDer Derivative of Smoothed
2657 CLF.Adjusted_Log Log of
2658 CLF.Adjusted_mva200 200 Day MA
2659 CLF.Adjusted_mva050 50 Day MA
2663 DGS30_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2664 DGS30_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 10-Year Treasury Constant Maturity Rate
2665 DGS30_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2667 DGS30_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2668 DGS30_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2672 DGS1_Smooth Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2673 DGS1_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2674 DGS1_SmoothDer Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2676 DGS1_mva200 1-Year Treasury Constant Maturity Rate 200 Day MA
2677 DGS1_mva050 1-Year Treasury Constant Maturity Rate 50 Day MA
2681 DGS2_Smooth Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2683 DGS2_SmoothDer Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2685 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2686 DGS2_mva050 2-Year Treasury Constant Maturity Rate 50 Day MA
2690 TB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2692 TB3MS_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2693 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2694 TB3MS_mva200 3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2695 TB3MS_mva050 3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2699 DTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2700 DTB3_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2701 DTB3_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2702 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2703 DTB3_mva200 3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2704 DTB3_mva050 3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2708 IRX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2709 IRX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2711 IRX.Open_Log Log of
2712 IRX.Open_mva200 200 Day MA
2713 IRX.Open_mva050 50 Day MA
2717 IRX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2718 IRX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2720 IRX.High_Log Log of
2721 IRX.High_mva200 200 Day MA
2722 IRX.High_mva050 50 Day MA
2726 IRX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2727 IRX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2728 IRX.Low_SmoothDer Derivative of Smoothed
2729 IRX.Low_Log Log of
2730 IRX.Low_mva200 200 Day MA
2731 IRX.Low_mva050 50 Day MA
2735 IRX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2736 IRX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2737 IRX.Close_SmoothDer Derivative of Smoothed
2738 IRX.Close_Log Log of
2739 IRX.Close_mva200 200 Day MA
2740 IRX.Close_mva050 50 Day MA
2741 IRX.Volume_YoY Year over Year
2742 IRX.Volume_YoY4 4 Year over 4 Year
2743 IRX.Volume_YoY5 5 Year over 5 Year
2744 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2745 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2746 IRX.Volume_SmoothDer Derivative of Smoothed
2747 IRX.Volume_Log Log of
2748 IRX.Volume_mva200 200 Day MA
2749 IRX.Volume_mva050 50 Day MA
2753 IRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2754 IRX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2755 IRX.Adjusted_SmoothDer Derivative of Smoothed
2756 IRX.Adjusted_Log Log of
2757 IRX.Adjusted_mva200 200 Day MA
2758 IRX.Adjusted_mva050 50 Day MA
2762 DCOILWTICO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2764 DCOILWTICO_SmoothDer Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2765 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2766 DCOILWTICO_mva200 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2767 DCOILWTICO_mva050 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 50 Day MA
2771 DCOILBRENTEU_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2773 DCOILBRENTEU_SmoothDer Derivative of Smoothed Crude Oil Prices: Brent - Europe
2775 DCOILBRENTEU_mva200 Crude Oil Prices: Brent - Europe 200 Day MA
2776 DCOILBRENTEU_mva050 Crude Oil Prices: Brent - Europe 50 Day MA
2783 NEWORDER_Log Log of Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
2784 NEWORDER_mva200 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2785 NEWORDER_mva050 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 50 Day MA
2798 ICSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Initial Jobless Claims
2800 ICSA_SmoothDer Derivative of Smoothed Initial Jobless Claims
2847 GSPC.Volume_mva200 200 Day MA
2894 FXAIX.Volume_YoY Year over Year
2895 FXAIX.Volume_YoY4 4 Year over 4 Year
2896 FXAIX.Volume_YoY5 5 Year over 5 Year
2897 FXAIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2898 FXAIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2899 FXAIX.Volume_SmoothDer Derivative of Smoothed
2900 FXAIX.Volume_Log Log of
2901 FXAIX.Volume_mva200 200 Day MA
2902 FXAIX.Volume_mva050 50 Day MA
2948 FTIHX.Volume_YoY Year over Year
2949 FTIHX.Volume_YoY4 4 Year over 4 Year
2950 FTIHX.Volume_YoY5 5 Year over 5 Year
2951 FTIHX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2952 FTIHX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2953 FTIHX.Volume_SmoothDer Derivative of Smoothed
2954 FTIHX.Volume_Log Log of
2955 FTIHX.Volume_mva200 200 Day MA
2956 FTIHX.Volume_mva050 50 Day MA
3002 MDIZX.Volume_YoY Year over Year
3003 MDIZX.Volume_YoY4 4 Year over 4 Year
3004 MDIZX.Volume_YoY5 5 Year over 5 Year
3005 MDIZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3006 MDIZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3007 MDIZX.Volume_SmoothDer Derivative of Smoothed
3008 MDIZX.Volume_Log Log of
3009 MDIZX.Volume_mva200 200 Day MA
3010 MDIZX.Volume_mva050 50 Day MA
3056 DODIX.Volume_YoY Year over Year
3057 DODIX.Volume_YoY4 4 Year over 4 Year
3058 DODIX.Volume_YoY5 5 Year over 5 Year
3059 DODIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3060 DODIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3061 DODIX.Volume_SmoothDer Derivative of Smoothed
3062 DODIX.Volume_Log Log of
3063 DODIX.Volume_mva200 200 Day MA
3064 DODIX.Volume_mva050 50 Day MA
3110 RLG.Volume_YoY Year over Year
3111 RLG.Volume_YoY4 4 Year over 4 Year
3112 RLG.Volume_YoY5 5 Year over 5 Year
3113 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3114 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3115 RLG.Volume_SmoothDer Derivative of Smoothed
3116 RLG.Volume_Log Log of
3117 RLG.Volume_mva200 200 Day MA
3118 RLG.Volume_mva050 50 Day MA
3224 STOXX50E.Volume_Log Log of
3279 EFA.Volume_mva200 200 Day MA
3296 GDP_Log Log of Gross Domestic Product
3297 GDP_mva200 Gross Domestic Product 200 Day MA
3298 GDP_mva050 Gross Domestic Product 50 Day MA
3299 FNDEFX_YoY Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) Year over Year
3305 FNDEFX_Log Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3306 FNDEFX_mva200 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3307 FNDEFX_mva050 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3313 FDEFX_SmoothDer Derivative of Smoothed Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3323 GDPNOW_Log Log of Fed Atlanta GDPNow
3341 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3342 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3343 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3387 VIG.Volume_mva200 200 Day MA
3401 WLRRAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3404 WLRRAL_Log Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3405 WLRRAL_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3406 WLRRAL_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 50 Day MA
3410 FEDFUNDS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Effective Federal Funds Rate
3412 FEDFUNDS_SmoothDer Derivative of Smoothed Effective Federal Funds Rate
3413 FEDFUNDS_Log Log of Effective Federal Funds Rate
3414 FEDFUNDS_mva200 Effective Federal Funds Rate 200 Day MA
3415 FEDFUNDS_mva050 Effective Federal Funds Rate 50 Day MA
3422 GPDI_Log Log of Gross Private Domestic Investment
3423 GPDI_mva200 Gross Private Domestic Investment 200 Day MA
3424 GPDI_mva050 Gross Private Domestic Investment 50 Day MA
3428 W790RC1Q027SBEA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Net domestic investment: Private: Domestic busines
3431 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3434 MZMV_YoY Velocity of MZM Money Stock Year over Year
3440 MZMV_Log Log of Velocity of MZM Money Stock
3441 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3442 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3449 M1_Log Log of M1 Money Stock
3450 M1_mva200 M1 Money Stock 200 Day MA
3451 M1_mva050 M1 Money Stock 50 Day MA
3458 M2_Log Log of M2 Money Stock
3459 M2_mva200 M2 Money Stock 200 Day MA
3460 M2_mva050 M2 Money Stock 50 Day MA
3466 OPHNFB_SmoothDer Derivative of Smoothed Nonfarm Business Sector: Real Output Per Hour of All Persons
3475 IPMAN_SmoothDer Derivative of Smoothed Industrial Production: Manufacturing (NAICS)
3476 IPMAN_Log Log of Industrial Production: Manufacturing (NAICS)
3477 IPMAN_mva200 Industrial Production: Manufacturing (NAICS) 200 Day MA
3478 IPMAN_mva050 Industrial Production: Manufacturing (NAICS) 50 Day MA
3533 GS5_YoY 5-Year Treasury Constant Maturity Rate Year over Year
3534 GS5_YoY4 5-Year Treasury Constant Maturity Rate 4 Year over 4 Year
3536 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3538 GS5_SmoothDer Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3539 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3540 GS5_mva200 5-Year Treasury Constant Maturity Rate 200 Day MA
3541 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3554 VIXCLS_Smooth Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3558 VIXCLS_mva200 CBOE Volatility Index 200 Day MA
3563 VXX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3581 VXX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3590 VXX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3598 VXX.Volume_YoY5 5 Year over 5 Year
3602 VXX.Volume_Log Log of
3608 VXX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3629 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3630 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3631 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
3656 MSPUS_Log Log of Median Sales Price of Houses Sold for the United States (NSA)
3657 MSPUS_mva200 Median Sales Price of Houses Sold for the United States (NSA) 200 Day MA
3658 MSPUS_mva050 Median Sales Price of Houses Sold for the United States (NSA) 50 Day MA
3674 DGORDER_Log Log of Manufacturers’ New Orders: Durable Goods (SA)
3675 DGORDER_mva200 Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3676 DGORDER_mva050 Manufacturers’ New Orders: Durable Goods (SA) 50 Day MA
3683 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3684 CSUSHPINSA_mva200 S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3685 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3686 GFDEGDQ188S_YoY Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
3692 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3693 GFDEGDQ188S_mva200 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 200 Day MA
3694 GFDEGDQ188S_mva050 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
3695 FYFSD_YoY Federal Surplus or Deficit Year over Year
3698 FYFSD_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Surplus or Deficit
3699 FYFSD_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit
3701 FYFSD_Log Log of Federal Surplus or Deficit
3702 FYFSD_mva200 Federal Surplus or Deficit 200 Day MA
3703 FYFSD_mva050 Federal Surplus or Deficit 50 Day MA
3704 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3710 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3711 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3712 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3718 GDX.Open_SmoothDer Derivative of Smoothed
3727 GDX.High_SmoothDer Derivative of Smoothed
3736 GDX.Low_SmoothDer Derivative of Smoothed
3745 GDX.Close_SmoothDer Derivative of Smoothed
3763 GDX.Adjusted_SmoothDer Derivative of Smoothed
3770 XLE.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3772 XLE.Open_SmoothDer Derivative of Smoothed
3774 XLE.Open_mva200 200 Day MA
3775 XLE.Open_mva050 50 Day MA
3779 XLE.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3781 XLE.High_SmoothDer Derivative of Smoothed
3783 XLE.High_mva200 200 Day MA
3784 XLE.High_mva050 50 Day MA
3788 XLE.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3790 XLE.Low_SmoothDer Derivative of Smoothed
3792 XLE.Low_mva200 200 Day MA
3793 XLE.Low_mva050 50 Day MA
3797 XLE.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3799 XLE.Close_SmoothDer Derivative of Smoothed
3801 XLE.Close_mva200 200 Day MA
3802 XLE.Close_mva050 50 Day MA
3815 XLE.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3817 XLE.Adjusted_SmoothDer Derivative of Smoothed
3819 XLE.Adjusted_mva200 200 Day MA
3820 XLE.Adjusted_mva050 50 Day MA
3824 GSG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3826 GSG.Open_SmoothDer Derivative of Smoothed
3828 GSG.Open_mva200 200 Day MA
3829 GSG.Open_mva050 50 Day MA
3833 GSG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3835 GSG.High_SmoothDer Derivative of Smoothed
3837 GSG.High_mva200 200 Day MA
3838 GSG.High_mva050 50 Day MA
3842 GSG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3844 GSG.Low_SmoothDer Derivative of Smoothed
3846 GSG.Low_mva200 200 Day MA
3847 GSG.Low_mva050 50 Day MA
3851 GSG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3853 GSG.Close_SmoothDer Derivative of Smoothed
3855 GSG.Close_mva200 200 Day MA
3856 GSG.Close_mva050 50 Day MA
3869 GSG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3871 GSG.Adjusted_SmoothDer Derivative of Smoothed
3873 GSG.Adjusted_mva200 200 Day MA
3874 GSG.Adjusted_mva050 50 Day MA
3876 WALCL_YoY4 All Federal Reserve Banks: Total Assets 4 Year over 4 Year
3882 WALCL_mva200 All Federal Reserve Banks: Total Assets 200 Day MA
3890 OUTMS_Log Log of Manufacturing Sector: Real Output
3891 OUTMS_mva200 Manufacturing Sector: Real Output 200 Day MA
3892 OUTMS_mva050 Manufacturing Sector: Real Output 50 Day MA
3896 MANEMP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
3899 MANEMP_Log Log of All Employees: Manufacturing
3900 MANEMP_mva200 All Employees: Manufacturing 200 Day MA
3901 MANEMP_mva050 All Employees: Manufacturing 50 Day MA
3904 PRS30006163_YoY5 Manufacturing Sector: Real Output Per Person 5 Year over 5 Year
3907 PRS30006163_SmoothDer Derivative of Smoothed Manufacturing Sector: Real Output Per Person
3914 BAMLC0A3CA_Smooth Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
3916 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
3918 BAMLC0A3CA_mva200 ICE BofAML US Corporate A Option-Adjusted Spread 200 Day MA
3919 BAMLC0A3CA_mva050 ICE BofAML US Corporate A Option-Adjusted Spread 50 Day MA
3920 AAA_YoY Moody’s Seasoned Aaa Corporate Bond Yield Year over Year
3921 AAA_YoY4 Moody’s Seasoned Aaa Corporate Bond Yield 4 Year over 4 Year
3923 AAA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
3925 AAA_SmoothDer Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
3926 AAA_Log Log of Moody’s Seasoned Aaa Corporate Bond Yield
3927 AAA_mva200 Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
3928 AAA_mva050 Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
3932 SOFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
3934 SOFR_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate
3936 SOFR_mva200 Secured Overnight Financing Rate 200 Day MA
3937 SOFR_mva050 Secured Overnight Financing Rate 50 Day MA
3941 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
3947 SOFR99_YoY Secured Overnight Financing Rate: 99th Percentile Year over Year
3949 SOFR99_YoY5 Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3950 SOFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
3952 SOFR99_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile
3953 SOFR99_Log Log of Secured Overnight Financing Rate: 99th Percentile
3954 SOFR99_mva200 Secured Overnight Financing Rate: 99th Percentile 200 Day MA
3955 SOFR99_mva050 Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3959 SOFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
3961 SOFR75_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
3963 SOFR75_mva200 Secured Overnight Financing Rate: 75th Percentile 200 Day MA
3964 SOFR75_mva050 Secured Overnight Financing Rate: 75th Percentile 50 Day MA
3965 SOFR25_YoY Secured Overnight Financing Rate: 25th Percentile Year over Year
3968 SOFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 25th Percentile
3970 SOFR25_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
3971 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
3972 SOFR25_mva200 Secured Overnight Financing Rate: 25th Percentile 200 Day MA
3973 SOFR25_mva050 Secured Overnight Financing Rate: 25th Percentile 50 Day MA
3977 SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 1st Percentile
3979 SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
3980 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
3981 SOFR1_mva200 Secured Overnight Financing Rate: 1st Percentile 200 Day MA
3982 SOFR1_mva050 Secured Overnight Financing Rate: 1st Percentile 50 Day MA
3986 OBFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
3988 OBFR_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate
3989 OBFR_Log Log of Overnight Bank Funding Rate
3990 OBFR_mva200 Overnight Bank Funding Rate 200 Day MA
3991 OBFR_mva050 Overnight Bank Funding Rate 50 Day MA
3992 OBFR99_YoY Overnight Bank Funding Rate: 99th Percentile Year over Year
3995 OBFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3996 OBFR99_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Overnight Bank Funding Rate: 99th Percentile
3997 OBFR99_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3998 OBFR99_Log Log of Overnight Bank Funding Rate: 99th Percentile
3999 OBFR99_mva200 Overnight Bank Funding Rate: 99th Percentile 200 Day MA
4000 OBFR99_mva050 Overnight Bank Funding Rate: 99th Percentile 50 Day MA
4004 OBFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 75th Percentile
4006 OBFR75_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
4007 OBFR75_Log Log of Overnight Bank Funding Rate: 75th Percentile
4008 OBFR75_mva200 Overnight Bank Funding Rate: 75th Percentile 200 Day MA
4009 OBFR75_mva050 Overnight Bank Funding Rate: 75th Percentile 50 Day MA
4013 OBFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
4015 OBFR25_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
4017 OBFR25_mva200 Overnight Bank Funding Rate: 25th Percentile 200 Day MA
4018 OBFR25_mva050 Overnight Bank Funding Rate: 25th Percentile 50 Day MA
4022 OBFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 1st Percentile
4024 OBFR1_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
4026 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
4027 OBFR1_mva050 Overnight Bank Funding Rate: 1st Percentile 50 Day MA
4033 RPONTSYD_SmoothDer Derivative of Smoothed Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4034 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4037 IOER_YoY Interest Rate on Excess Reserves Year over Year
4043 IOER_Log Log of Interest Rate on Excess Reserves
4044 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
4045 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
4055 EXCSRESNW_YoY Excess Reserves of Depository Institutions Year over Year
4061 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
4062 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
4063 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
4064 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4070 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
4071 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4072 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4079 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4080 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4081 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4085 CEU0600000007_Smooth Savitsky-Golay Smoothed (p=3, n=365) Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4087 CEU0600000007_SmoothDer Derivative of Smoothed Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4088 CEU0600000007_Log Log of Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4090 CEU0600000007_mva050 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 50 Day MA
4097 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
4098 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4099 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4103 WCURRNS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
4105 WCURRNS_SmoothDer Derivative of Smoothed Currency Component of M1
4106 WCURRNS_Log Log of Currency Component of M1
4107 WCURRNS_mva200 Currency Component of M1 200 Day MA
4108 WCURRNS_mva050 Currency Component of M1 50 Day MA
4120 PRS88003193_YoY5 Nonfinancial Corporations Sector: Unit Profits 5 Year over 5 Year
4123 PRS88003193_SmoothDer Derivative of Smoothed Nonfinancial Corporations Sector: Unit Profits
4130 PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index for All Commodities
4132 PPIACO_SmoothDer Derivative of Smoothed Producer Price Index for All Commodities
4133 PPIACO_Log Log of Producer Price Index for All Commodities
4134 PPIACO_mva200 Producer Price Index for All Commodities 200 Day MA
4135 PPIACO_mva050 Producer Price Index for All Commodities 50 Day MA
4139 PCUOMFGOMFG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
4141 PCUOMFGOMFG_SmoothDer Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4142 PCUOMFGOMFG_Log Log of Producer Price Index by Industry: Total Manufacturing Industries
4143 PCUOMFGOMFG_mva200 Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
4144 PCUOMFGOMFG_mva050 Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
4151 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4152 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4157 POPTHM_Log Log of Population (U.S.)
4158 POPTHM_Log Log of Population (U.S.)
4159 POPTHM_mva200 Population (U.S.) 200 Day MA
4160 POPTHM_mva200 Population (U.S.) 200 Day MA
4161 POPTHM_mva050 Population (U.S.) 50 Day MA
4162 POPTHM_mva050 Population (U.S.) 50 Day MA
4169 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4170 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4175 POPTHM.1_Log Log of
4176 POPTHM.1_Log Log of
4177 POPTHM.1_mva200 200 Day MA
4178 POPTHM.1_mva200 200 Day MA
4179 POPTHM.1_mva050 50 Day MA
4180 POPTHM.1_mva050 50 Day MA
4188 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
4189 CLF16OV_mva050 Civilian Labor Force Level, SA 50 Day MA
4195 LNU01000000_SmoothDer Derivative of Smoothed Civilian Labor Force Level, NSA
4197 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
4198 LNU01000000_mva050 Civilian Labor Force Level, NSA 50 Day MA
4204 LNU03000000_SmoothDer Derivative of Smoothed Unemployment Level (NSA)
4208 UNEMPLOY_YoY Unemployment Level, seasonally adjusted Year over Year
4213 UNEMPLOY_SmoothDer Derivative of Smoothed Unemployment Level, seasonally adjusted
4222 RSAFS_SmoothDer Derivative of Smoothed Advance Retail Sales: Retail and Food Services
4224 RSAFS_mva200 Advance Retail Sales: Retail and Food Services 200 Day MA
4229 FRGSHPUSM649NCIS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cass Freight Index: Shipments
4231 FRGSHPUSM649NCIS_SmoothDer Derivative of Smoothed Cass Freight Index: Shipments
4232 FRGSHPUSM649NCIS_Log Log of Cass Freight Index: Shipments
4234 FRGSHPUSM649NCIS_mva050 Cass Freight Index: Shipments 50 Day MA
4238 BOPGTB_Smooth Savitsky-Golay Smoothed (p=3, n=365) Trade Balance: Goods, Balance of Payments Basis (SA)
4240 BOPGTB_SmoothDer Derivative of Smoothed Trade Balance: Goods, Balance of Payments Basis (SA)
4241 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4245 TERMCBPER24NS_YoY4 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 4 Year over 4 Year
4249 TERMCBPER24NS_SmoothDer Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4250 TERMCBPER24NS_Log Log of Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4251 TERMCBPER24NS_mva200 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 200 Day MA
4252 TERMCBPER24NS_mva050 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 50 Day MA
4259 A065RC1A027NBEA_Log Log of Personal income (NSA)
4260 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
4261 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
4268 PI_Log Log of Personal income (SA)
4269 PI_mva200 Personal income (SA) 200 Day MA
4270 PI_mva050 Personal income (SA) 50 Day MA
4274 PCE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures (SA)
4276 PCE_SmoothDer Derivative of Smoothed Personal Consumption Expenditures (SA)
4277 PCE_Log Log of Personal Consumption Expenditures (SA)
4278 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
4279 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
4285 A053RC1Q027SBEA_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj)
4286 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
4287 A053RC1Q027SBEA_mva200 National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4288 A053RC1Q027SBEA_mva050 National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4294 CPROFIT_SmoothDer Derivative of Smoothed Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4341 SPY.Volume_mva200 200 Day MA
4448 EES.Volume_Log Log of
4449 EES.Volume_mva200 200 Day MA
4503 IJR.Volume_mva200 200 Day MA
4550 VGSTX.Volume_YoY Year over Year
4551 VGSTX.Volume_YoY4 4 Year over 4 Year
4552 VGSTX.Volume_YoY5 5 Year over 5 Year
4553 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4554 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4555 VGSTX.Volume_SmoothDer Derivative of Smoothed
4556 VGSTX.Volume_Log Log of
4557 VGSTX.Volume_mva200 200 Day MA
4558 VGSTX.Volume_mva050 50 Day MA
4604 VFINX.Volume_YoY Year over Year
4605 VFINX.Volume_YoY4 4 Year over 4 Year
4606 VFINX.Volume_YoY5 5 Year over 5 Year
4607 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4608 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4609 VFINX.Volume_SmoothDer Derivative of Smoothed
4610 VFINX.Volume_Log Log of
4611 VFINX.Volume_mva200 200 Day MA
4612 VFINX.Volume_mva050 50 Day MA
4663 VOE.Volume_SmoothDer Derivative of Smoothed
4665 VOE.Volume_mva200 200 Day MA
4666 VOE.Volume_mva050 50 Day MA
4719 VOT.Volume_mva200 200 Day MA
4731 TMFGX.Open_YoY4 4 Year over 4 Year
4732 TMFGX.Open_YoY5 5 Year over 5 Year
4736 TMFGX.Open_Log Log of
4740 TMFGX.High_YoY4 4 Year over 4 Year
4741 TMFGX.High_YoY5 5 Year over 5 Year
4745 TMFGX.High_Log Log of
4749 TMFGX.Low_YoY4 4 Year over 4 Year
4750 TMFGX.Low_YoY5 5 Year over 5 Year
4754 TMFGX.Low_Log Log of
4758 TMFGX.Close_YoY4 4 Year over 4 Year
4759 TMFGX.Close_YoY5 5 Year over 5 Year
4763 TMFGX.Close_Log Log of
4766 TMFGX.Volume_YoY Year over Year
4767 TMFGX.Volume_YoY4 4 Year over 4 Year
4768 TMFGX.Volume_YoY5 5 Year over 5 Year
4769 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4770 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4771 TMFGX.Volume_SmoothDer Derivative of Smoothed
4772 TMFGX.Volume_Log Log of
4773 TMFGX.Volume_mva200 200 Day MA
4774 TMFGX.Volume_mva050 50 Day MA
4776 TMFGX.Adjusted_YoY4 4 Year over 4 Year
4777 TMFGX.Adjusted_YoY5 5 Year over 5 Year
4781 TMFGX.Adjusted_Log Log of
4874 ONEQ.Volume_YoY Year over Year
4875 ONEQ.Volume_YoY4 4 Year over 4 Year
4881 ONEQ.Volume_mva200 200 Day MA
4882 ONEQ.Volume_mva050 50 Day MA
4928 FSMAX.Volume_YoY Year over Year
4929 FSMAX.Volume_YoY4 4 Year over 4 Year
4930 FSMAX.Volume_YoY5 5 Year over 5 Year
4931 FSMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4932 FSMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4933 FSMAX.Volume_SmoothDer Derivative of Smoothed
4934 FSMAX.Volume_Log Log of
4935 FSMAX.Volume_mva200 200 Day MA
4936 FSMAX.Volume_mva050 50 Day MA
4982 FXNAX.Volume_YoY Year over Year
4983 FXNAX.Volume_YoY4 4 Year over 4 Year
4984 FXNAX.Volume_YoY5 5 Year over 5 Year
4985 FXNAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4986 FXNAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4987 FXNAX.Volume_SmoothDer Derivative of Smoothed
4988 FXNAX.Volume_Log Log of
4989 FXNAX.Volume_mva200 200 Day MA
4990 FXNAX.Volume_mva050 50 Day MA
5036 HAINX.Volume_YoY Year over Year
5037 HAINX.Volume_YoY4 4 Year over 4 Year
5038 HAINX.Volume_YoY5 5 Year over 5 Year
5039 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5040 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5041 HAINX.Volume_SmoothDer Derivative of Smoothed
5042 HAINX.Volume_Log Log of
5043 HAINX.Volume_mva200 200 Day MA
5044 HAINX.Volume_mva050 50 Day MA
5090 HNACX.Volume_YoY Year over Year
5091 HNACX.Volume_YoY4 4 Year over 4 Year
5092 HNACX.Volume_YoY5 5 Year over 5 Year
5093 HNACX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5094 HNACX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5095 HNACX.Volume_SmoothDer Derivative of Smoothed
5096 HNACX.Volume_Log Log of
5097 HNACX.Volume_mva200 200 Day MA
5098 HNACX.Volume_mva050 50 Day MA
5151 VEU.Volume_mva200 200 Day MA
5167 VEIRX.Open_SmoothDer Derivative of Smoothed
5176 VEIRX.High_SmoothDer Derivative of Smoothed
5185 VEIRX.Low_SmoothDer Derivative of Smoothed
5194 VEIRX.Close_SmoothDer Derivative of Smoothed
5198 VEIRX.Volume_YoY Year over Year
5199 VEIRX.Volume_YoY4 4 Year over 4 Year
5200 VEIRX.Volume_YoY5 5 Year over 5 Year
5201 VEIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5202 VEIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5203 VEIRX.Volume_SmoothDer Derivative of Smoothed
5204 VEIRX.Volume_Log Log of
5205 VEIRX.Volume_mva200 200 Day MA
5206 VEIRX.Volume_mva050 50 Day MA
5219 BIL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5221 BIL.Open_SmoothDer Derivative of Smoothed
5224 BIL.Open_mva050 50 Day MA
5228 BIL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5230 BIL.High_SmoothDer Derivative of Smoothed
5233 BIL.High_mva050 50 Day MA
5237 BIL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5239 BIL.Low_SmoothDer Derivative of Smoothed
5246 BIL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5248 BIL.Close_SmoothDer Derivative of Smoothed
5251 BIL.Close_mva050 50 Day MA
5255 BIL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5257 BIL.Volume_SmoothDer Derivative of Smoothed
5259 BIL.Volume_mva200 200 Day MA
5264 BIL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5265 BIL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5266 BIL.Adjusted_SmoothDer Derivative of Smoothed
5267 BIL.Adjusted_Log Log of
5269 BIL.Adjusted_mva050 50 Day MA
5312 IVOO.Volume_Log Log of
5362 VO.Volume_YoY5 5 Year over 5 Year
5366 VO.Volume_Log Log of
5367 VO.Volume_mva200 200 Day MA
5417 CZA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5420 CZA.Volume_Log Log of
5470 VYM.Volume_YoY5 5 Year over 5 Year
5475 VYM.Volume_mva200 200 Day MA
5576 SLY.Volume_YoY Year over Year
5582 SLY.Volume_Log Log of
5583 SLY.Volume_mva200 200 Day MA
5637 QQQ.Volume_mva200 200 Day MA
5687 HYMB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5688 HYMB.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5689 HYMB.Volume_SmoothDer Derivative of Smoothed
5690 HYMB.Volume_Log Log of
5691 HYMB.Volume_mva200 200 Day MA
5692 HYMB.Volume_mva050 50 Day MA
5707 GOLD.Open_SmoothDer Derivative of Smoothed
5708 GOLD.Open_Log Log of
5709 GOLD.Open_mva200 200 Day MA
5716 GOLD.High_SmoothDer Derivative of Smoothed
5718 GOLD.High_mva200 200 Day MA
5725 GOLD.Low_SmoothDer Derivative of Smoothed
5727 GOLD.Low_mva200 200 Day MA
5734 GOLD.Close_SmoothDer Derivative of Smoothed
5736 GOLD.Close_mva200 200 Day MA
5744 GOLD.Volume_Log Log of
5752 GOLD.Adjusted_SmoothDer Derivative of Smoothed
5754 GOLD.Adjusted_mva200 200 Day MA
5759 BKR.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5761 BKR.Open_SmoothDer Derivative of Smoothed
5762 BKR.Open_Log Log of
5763 BKR.Open_mva200 200 Day MA
5768 BKR.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5770 BKR.High_SmoothDer Derivative of Smoothed
5772 BKR.High_mva200 200 Day MA
5777 BKR.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5779 BKR.Low_SmoothDer Derivative of Smoothed
5781 BKR.Low_mva200 200 Day MA
5786 BKR.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5788 BKR.Close_SmoothDer Derivative of Smoothed
5790 BKR.Close_mva200 200 Day MA
5798 BKR.Volume_Log Log of
5799 BKR.Volume_mva200 200 Day MA
5804 BKR.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5806 BKR.Adjusted_SmoothDer Derivative of Smoothed
5808 BKR.Adjusted_mva200 200 Day MA
5813 SLB.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5815 SLB.Open_SmoothDer Derivative of Smoothed
5817 SLB.Open_mva200 200 Day MA
5818 SLB.Open_mva050 50 Day MA
5822 SLB.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5824 SLB.High_SmoothDer Derivative of Smoothed
5826 SLB.High_mva200 200 Day MA
5827 SLB.High_mva050 50 Day MA
5831 SLB.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5833 SLB.Low_SmoothDer Derivative of Smoothed
5835 SLB.Low_mva200 200 Day MA
5840 SLB.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5842 SLB.Close_SmoothDer Derivative of Smoothed
5844 SLB.Close_mva200 200 Day MA
5853 SLB.Volume_mva200 200 Day MA
5858 SLB.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5860 SLB.Adjusted_SmoothDer Derivative of Smoothed
5862 SLB.Adjusted_mva200 200 Day MA
5867 HAL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5869 HAL.Open_SmoothDer Derivative of Smoothed
5870 HAL.Open_Log Log of
5871 HAL.Open_mva200 200 Day MA
5876 HAL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5878 HAL.High_SmoothDer Derivative of Smoothed
5880 HAL.High_mva200 200 Day MA
5885 HAL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5887 HAL.Low_SmoothDer Derivative of Smoothed
5889 HAL.Low_mva200 200 Day MA
5894 HAL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5896 HAL.Close_SmoothDer Derivative of Smoothed
5898 HAL.Close_mva200 200 Day MA
5906 HAL.Volume_Log Log of
5907 HAL.Volume_mva200 200 Day MA
5912 HAL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5914 HAL.Adjusted_SmoothDer Derivative of Smoothed
5916 HAL.Adjusted_mva200 200 Day MA
5921 IP.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5923 IP.Open_SmoothDer Derivative of Smoothed
5924 IP.Open_Log Log of
5930 IP.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5932 IP.High_SmoothDer Derivative of Smoothed
5939 IP.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5941 IP.Low_SmoothDer Derivative of Smoothed
5948 IP.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5950 IP.Close_SmoothDer Derivative of Smoothed
5961 IP.Volume_mva200 200 Day MA
5966 IP.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5968 IP.Adjusted_SmoothDer Derivative of Smoothed
5975 PKG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5977 PKG.Open_SmoothDer Derivative of Smoothed
5979 PKG.Open_mva200 200 Day MA
5984 PKG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5986 PKG.High_SmoothDer Derivative of Smoothed
5988 PKG.High_mva200 200 Day MA
5993 PKG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5995 PKG.Low_SmoothDer Derivative of Smoothed
5997 PKG.Low_mva200 200 Day MA
6002 PKG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6004 PKG.Close_SmoothDer Derivative of Smoothed
6006 PKG.Close_mva200 200 Day MA
6020 PKG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6022 PKG.Adjusted_SmoothDer Derivative of Smoothed
6024 PKG.Adjusted_mva200 200 Day MA
6067 UPS.Volume_SmoothDer Derivative of Smoothed
6069 UPS.Volume_mva200 200 Day MA
6085 FDX.Open_SmoothDer Derivative of Smoothed
6094 FDX.High_SmoothDer Derivative of Smoothed
6103 FDX.Low_SmoothDer Derivative of Smoothed
6112 FDX.Close_SmoothDer Derivative of Smoothed
6119 FDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6120 FDX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6130 FDX.Adjusted_SmoothDer Derivative of Smoothed
6137 T.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6139 T.Open_SmoothDer Derivative of Smoothed
6140 T.Open_Log Log of
6142 T.Open_mva050 50 Day MA
6146 T.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6148 T.High_SmoothDer Derivative of Smoothed
6155 T.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6157 T.Low_SmoothDer Derivative of Smoothed
6164 T.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6166 T.Close_SmoothDer Derivative of Smoothed
6182 T.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6184 T.Adjusted_SmoothDer Derivative of Smoothed
6193 VZ.Open_SmoothDer Derivative of Smoothed
6202 VZ.High_SmoothDer Derivative of Smoothed
6211 VZ.Low_SmoothDer Derivative of Smoothed
6220 VZ.Close_SmoothDer Derivative of Smoothed
6238 VZ.Adjusted_SmoothDer Derivative of Smoothed
6247 ISMMANPMI_SmoothDer Derivative of Smoothed Institute of Supply Managment PMI Composite Index
6256 MULTPLSP500PERATIOMONTH_SmoothDer Derivative of Smoothed S&P 500 TTM P/E
6266 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
6267 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
6268 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
6269 MULTPLSP500DIVYIELDMONTH_YoY S&P 500 Dividend Yield by Month Year over Year
6270 MULTPLSP500DIVYIELDMONTH_YoY4 S&P 500 Dividend Yield by Month 4 Year over 4 Year
6271 MULTPLSP500DIVYIELDMONTH_YoY5 S&P 500 Dividend Yield by Month 5 Year over 5 Year
6272 MULTPLSP500DIVYIELDMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend Yield by Month
6274 MULTPLSP500DIVYIELDMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend Yield by Month
6275 MULTPLSP500DIVYIELDMONTH_Log Log of S&P 500 Dividend Yield by Month
6276 MULTPLSP500DIVYIELDMONTH_mva200 S&P 500 Dividend Yield by Month 200 Day MA
6277 MULTPLSP500DIVYIELDMONTH_mva050 S&P 500 Dividend Yield by Month 50 Day MA
6278 MULTPLSP500DIVMONTH_YoY S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
6290 CHRISCMEHG1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6292 CHRISCMEHG1_SmoothDer Derivative of Smoothed Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6293 CHRISCMEHG1_Log Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6295 CHRISCMEHG1_mva050 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
6296 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
6302 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
6303 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
6304 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
6312 LBMAGOLD.USD_AM_mva200 200 Day MA
6321 LBMAGOLD.USD_PM_mva200 200 Day MA
6326 LBMAGOLD.GBP_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6328 LBMAGOLD.GBP_AM_SmoothDer Derivative of Smoothed
6330 LBMAGOLD.GBP_AM_mva200 200 Day MA
6335 LBMAGOLD.GBP_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6337 LBMAGOLD.GBP_PM_SmoothDer Derivative of Smoothed
6339 LBMAGOLD.GBP_PM_mva200 200 Day MA
6346 LBMAGOLD.EURO_AM_SmoothDer Derivative of Smoothed
6348 LBMAGOLD.EURO_AM_mva200 200 Day MA
6355 LBMAGOLD.EURO_PM_SmoothDer Derivative of Smoothed
6357 LBMAGOLD.EURO_PM_mva200 200 Day MA
6359 PETA103600001M_YoY U.S. Total Gasoline Retail Sales by Refiners, Monthly Year over Year
6366 PETA103600001M_mva200 U.S. Total Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6368 PETA123600001M_YoY U.S. Regular Gasoline Retail Sales by Refiners, Monthly Year over Year
6374 PETA123600001M_Log Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
6375 PETA123600001M_mva200 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6376 PETA123600001M_mva050 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6377 PETA143B00001M_YoY U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
6378 PETA143B00001M_YoY4 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
6379 PETA143B00001M_YoY5 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
6383 PETA143B00001M_Log Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
6384 PETA143B00001M_mva200 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6385 PETA143B00001M_mva050 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6401 TOTALOGNRPUSM_Log Log of Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6402 TOTALOGNRPUSM_mva200 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 200 Day MA
6403 TOTALOGNRPUSM_mva050 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 50 Day MA
6410 TOTALPANRPUSM_Log Log of Crude Oil Rotary Rigs in Operation, Monthly
6411 TOTALPANRPUSM_mva200 Crude Oil Rotary Rigs in Operation, Monthly 200 Day MA
6412 TOTALPANRPUSM_mva050 Crude Oil Rotary Rigs in Operation, Monthly 50 Day MA
6414 TOTALNGNRPUSM_YoY4 Natural Gas Rotary Rigs in Operation, Monthly 4 Year over 4 Year
6418 TOTALNGNRPUSM_SmoothDer Derivative of Smoothed Natural Gas Rotary Rigs in Operation, Monthly
6419 TOTALNGNRPUSM_Log Log of Natural Gas Rotary Rigs in Operation, Monthly
6420 TOTALNGNRPUSM_mva200 Natural Gas Rotary Rigs in Operation, Monthly 200 Day MA
6421 TOTALNGNRPUSM_mva050 Natural Gas Rotary Rigs in Operation, Monthly 50 Day MA
6428 BKRTotal_Log Log of Total Rig Count
6429 BKRTotal_mva200 Total Rig Count 200 Day MA
6430 BKRTotal_mva050 Total Rig Count 50 Day MA
6434 BKRGas_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gas Rig Count
6436 BKRGas_SmoothDer Derivative of Smoothed Gas Rig Count
6437 BKRGas_Log Log of Gas Rig Count
6438 BKRGas_mva200 Gas Rig Count 200 Day MA
6439 BKRGas_mva050 Gas Rig Count 50 Day MA
6446 BKROil_Log Log of Oil Rig Count
6447 BKROil_mva200 Oil Rig Count 200 Day MA
6448 BKROil_mva050 Oil Rig Count 50 Day MA
6449 FARMINCOME_YoY Net Farm Income Year over Year
6455 FARMINCOME_Log Log of Net Farm Income
6456 FARMINCOME_mva200 Net Farm Income 200 Day MA
6457 FARMINCOME_mva050 Net Farm Income 50 Day MA
6464 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
6465 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
6466 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
6473 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
6474 AREARNINGSPERSHARE_mva200 As-Reported Earnings per Share 200 Day MA
6475 AREARNINGSPERSHARE_mva050 As-Reported Earnings per Share 50 Day MA
6476 CASHDIVIDENDSPERSHR_YoY Cash Dividends per Share Year over Year
6482 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
6483 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
6484 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
6491 SALESPERSHR_Log Log of Sales per Share
6492 SALESPERSHR_mva200 Sales per Share 200 Day MA
6493 SALESPERSHR_mva050 Sales per Share 50 Day MA
6500 BOOKVALPERSHR_Log Log of Book value per Share
6501 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
6502 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
6509 CAPEXPERSHR_Log Log of Cap ex per Share
6510 CAPEXPERSHR_mva200 Cap ex per Share 200 Day MA
6511 CAPEXPERSHR_mva050 Cap ex per Share 50 Day MA
6518 PRICE_Log Log of Price
6519 PRICE_mva200 Price 200 Day MA
6520 PRICE_mva050 Price 50 Day MA
6527 OPEARNINGSTTM_Log Log of TTM Operating Earnings
6528 OPEARNINGSTTM_mva200 TTM Operating Earnings 200 Day MA
6529 OPEARNINGSTTM_mva050 TTM Operating Earnings 50 Day MA
6536 AREARNINGSTTM_Log Log of TTM Reported Earnings
6537 AREARNINGSTTM_mva200 TTM Reported Earnings 200 Day MA
6538 AREARNINGSTTM_mva050 TTM Reported Earnings 50 Day MA
6545 FINRAMarginDebt_Log Log of Margin Debt
6547 FINRAMarginDebt_mva050 Margin Debt 50 Day MA
6553 FINRAFreeCreditMargin_SmoothDer Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
6554 FINRAFreeCreditMargin_Log Log of Free Credit Balances in Customers’ Securities Margin Accounts
6556 FINRAFreeCreditMargin_mva050 Free Credit Balances in Customers’ Securities Margin Accounts 50 Day MA
6557 OCCEquityVolume_YoY Equity Options Volume Year over Year
6563 OCCEquityVolume_Log Log of Equity Options Volume
6564 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
6565 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
6566 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
6572 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
6573 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
6574 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
6580 RSALESAGG_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
6582 RSALESAGG_mva200 Real Retail and Food Services Sales (RRSFS and RSALES) 200 Day MA
6590 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
6599 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
6602 BUSLOANS.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6604 BUSLOANS.by.GDP_YoY5 Business Loans Normalized by GDP 5 Year over 5 Year
6605 BUSLOANS.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6607 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6608 BUSLOANS.by.GDP_Log Log of Business Loans Normalized by GDP
6609 BUSLOANS.by.GDP_mva200 Business Loans Normalized by GDP 200 Day MA
6610 BUSLOANS.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6614 BUSLOANS.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
6616 BUSLOANS.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
6618 BUSLOANS.INTEREST_mva200 Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
6619 BUSLOANS.INTEREST_mva050 Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
6623 BUSLOANS.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6625 BUSLOANS.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6627 BUSLOANS.INTEREST.by.GDP_mva200 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
6628 BUSLOANS.INTEREST.by.GDP_mva050 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
6629 BUSLOANSNSA.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6631 BUSLOANSNSA.by.GDP_YoY5 Business Loans Normalized by GDP 5 Year over 5 Year
6632 BUSLOANSNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6634 BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6635 BUSLOANSNSA.by.GDP_Log Log of Business Loans Normalized by GDP
6636 BUSLOANSNSA.by.GDP_mva200 Business Loans Normalized by GDP 200 Day MA
6637 BUSLOANSNSA.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6638 TOTCI.by.GDP_YoY Business Loans (Weekly, SA) Normalized by GDP Year over Year
6641 TOTCI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, SA) Normalized by GDP
6643 TOTCI.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6644 TOTCI.by.GDP_Log Log of Business Loans (Weekly, SA) Normalized by GDP
6645 TOTCI.by.GDP_mva200 Business Loans (Weekly, SA) Normalized by GDP 200 Day MA
6646 TOTCI.by.GDP_mva050 Business Loans (Weekly, SA) Normalized by GDP 50 Day MA
6647 TOTCINSA.by.GDP_YoY Business Loans (Weekly, NSA) Normalized by GDP Year over Year
6650 TOTCINSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
6652 TOTCINSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
6653 TOTCINSA.by.GDP_Log Log of Business Loans (Weekly, NSA) Normalized by GDP
6654 TOTCINSA.by.GDP_mva200 Business Loans (Weekly, NSA) Normalized by GDP 200 Day MA
6655 TOTCINSA.by.GDP_mva050 Business Loans (Weekly, NSA) Normalized by GDP 50 Day MA
6659 TOTCINSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6661 TOTCINSA.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
6663 TOTCINSA.INTEREST_mva200 Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
6664 TOTCINSA.INTEREST_mva050 Business Loans (Weekly, NSA) Adjusted Interest Burdens 50 Day MA
6668 TOTCINSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6670 TOTCINSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6672 TOTCINSA.INTEREST.by.GDP_mva200 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
6673 TOTCINSA.INTEREST.by.GDP_mva050 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 50 Day MA
6674 W875RX1.by.GDP_YoY Real Personal Income Normalized by GDP Year over Year
6676 W875RX1.by.GDP_YoY5 Real Personal Income Normalized by GDP 5 Year over 5 Year
6679 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
6680 W875RX1.by.GDP_Log Log of Real Personal Income Normalized by GDP
6683 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
6688 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6694 PI.by.GDP_YoY5 Personal Income (SA) Normalized by GDP 5 Year over 5 Year
6698 PI.by.GDP_Log Log of Personal Income (SA) Normalized by GDP
6700 PI.by.GDP_mva050 Personal Income (SA) Normalized by GDP 50 Day MA
6706 A053RC1Q027SBEA.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6707 A053RC1Q027SBEA.by.GDP_Log Log of National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6709 A053RC1Q027SBEA.by.GDP_mva050 National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 50 Day MA
6715 CPROFIT.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6722 CONSUMERNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6724 CONSUMERNSA.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
6725 CONSUMERNSA.by.GDP_Log Log of Consumer Loans Not Seasonally Adjusted divided by GDP
6726 CONSUMERNSA.by.GDP_mva200 Consumer Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6727 CONSUMERNSA.by.GDP_mva050 Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6728 RREACBM027NBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6731 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6733 RREACBM027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
6734 RREACBM027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, NSA) divided by GDP
6736 RREACBM027NBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, NSA) divided by GDP 50 Day MA
6737 RREACBM027SBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6738 RREACBM027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6739 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6740 RREACBM027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6742 RREACBM027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6743 RREACBM027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
6744 RREACBM027SBOG.by.GDP_mva200 Residental Real Estate Loans (Monthly, SA) divided by GDP 200 Day MA
6745 RREACBM027SBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
6746 RREACBW027SBOG.by.GDP_YoY Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
6749 RREACBW027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6751 RREACBW027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6752 RREACBW027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Weekly, SA) divided by GDP
6753 RREACBW027SBOG.by.GDP_mva200 Residental Real Estate Loans (Weekly, SA) divided by GDP 200 Day MA
6754 RREACBW027SBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, SA) divided by GDP 50 Day MA
6755 RREACBW027NBOG.by.GDP_YoY Residental Real Estate Loans (Weekly, NSA) divided by GDP Year over Year
6757 RREACBW027NBOG.by.GDP_YoY5 Residental Real Estate Loans (Weekly, NSA) divided by GDP 5 Year over 5 Year
6758 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6760 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6761 RREACBW027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Weekly, NSA) divided by GDP
6763 RREACBW027NBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
6779 DGORDER.by.GDP_Log Log of Durable Goods (Monthly, NSA) divided by GDP
6780 DGORDER.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6781 DGORDER.by.GDP_mva050 Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
6784 ASHMA.by.GDP_YoY5 Home Mortgages (Quarterly, NSA) divided by GDP 5 Year over 5 Year
6787 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6788 ASHMA.by.GDP_Log Log of Home Mortgages (Quarterly, NSA) divided by GDP
6790 ASHMA.by.GDP_mva050 Home Mortgages (Quarterly, NSA) divided by GDP 50 Day MA
6791 ASHMA.INTEREST_YoY Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Year over Year
6792 ASHMA.INTEREST_YoY4 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6793 ASHMA.INTEREST_YoY5 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6794 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6795 ASHMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6796 ASHMA.INTEREST_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6797 ASHMA.INTEREST_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6798 ASHMA.INTEREST_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6799 ASHMA.INTEREST_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6800 ASHMA.INTEREST.by.GDP_YoY Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP Year over Year
6801 ASHMA.INTEREST.by.GDP_YoY4 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 4 Year over 4 Year
6802 ASHMA.INTEREST.by.GDP_YoY5 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 5 Year over 5 Year
6803 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6804 ASHMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6805 ASHMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6806 ASHMA.INTEREST.by.GDP_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6807 ASHMA.INTEREST.by.GDP_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 200 Day MA
6808 ASHMA.INTEREST.by.GDP_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 50 Day MA
6810 CONSUMERNSA.INTEREST_YoY4 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 4 Year over 4 Year
6811 CONSUMERNSA.INTEREST_YoY5 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 5 Year over 5 Year
6814 CONSUMERNSA.INTEREST_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6815 CONSUMERNSA.INTEREST_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6816 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6817 CONSUMERNSA.INTEREST_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
6819 CONSUMERNSA.INTEREST.by.GDP_YoY4 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 4 Year over 4 Year
6820 CONSUMERNSA.INTEREST.by.GDP_YoY5 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 5 Year over 5 Year
6823 CONSUMERNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6824 CONSUMERNSA.INTEREST.by.GDP_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6825 CONSUMERNSA.INTEREST.by.GDP_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 200 Day MA
6826 CONSUMERNSA.INTEREST.by.GDP_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 50 Day MA
6830 TOTLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6833 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6834 TOTLNNSA_mva200 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
6835 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6836 TOTLNNSA.by.GDP_YoY Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6839 TOTLNNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
6841 TOTLNNSA.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6842 TOTLNNSA.by.GDP_Log Log of Total Loans Not Seasonally Adjusted divided by GDP
6843 TOTLNNSA.by.GDP_mva200 Total Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6844 TOTLNNSA.by.GDP_mva050 Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6848 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6850 TOTLNNSA.INTEREST_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
6852 TOTLNNSA.INTEREST_mva200 Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
6853 TOTLNNSA.INTEREST_mva050 Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
6857 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6859 TOTLNNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6861 TOTLNNSA.INTEREST.by.GDP_mva200 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
6862 TOTLNNSA.INTEREST.by.GDP_mva050 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
6872 EXCSRESNW.by.GDP_YoY Excess Reserves of Depository Institutions Divided by GDP Year over Year
6877 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6884 WLRRAL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6887 WLRRAL.by.GDP_Log Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6888 WLRRAL.by.GDP_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6889 WLRRAL.by.GDP_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 50 Day MA
6893 SOFR99.minus.SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6895 SOFR99.minus.SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6897 SOFR99.minus.SOFR1_mva200 Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 200 Day MA
6902 EXPCH.minus.IMPCH_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6904 EXPCH.minus.IMPCH_SmoothDer Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6905 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6907 EXPCH.minus.IMPCH_mva050 U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 50 Day MA
6914 EXPMX.minus.IMPMX_Log Log of
6918 SRPSABSNNCB.by.GDP_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6919 SRPSABSNNCB.by.GDP_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 5 Year over 5 Year
6923 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6924 SRPSABSNNCB.by.GDP_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 200 Day MA
6925 SRPSABSNNCB.by.GDP_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 50 Day MA
6932 ASTLL.by.GDP_Log Log of All sectors; total loans; liability, Level (NSA) Divided by GDP
6933 ASTLL.by.GDP_mva200 All sectors; total loans; liability, Level (NSA) Divided by GDP 200 Day MA
6934 ASTLL.by.GDP_mva050 All sectors; total loans; liability, Level (NSA) Divided by GDP 50 Day MA
6935 ASFMA.by.GDP_YoY All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6940 ASFMA.by.GDP_SmoothDer Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6944 ASFMA.by.ASTLL_YoY All sectors; total loans Divided by farm mortgages Year over Year
6949 ASFMA.by.ASTLL_SmoothDer Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6953 ASFMA.INTEREST_YoY Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Year over Year
6954 ASFMA.INTEREST_YoY4 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6955 ASFMA.INTEREST_YoY5 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6956 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6957 ASFMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6958 ASFMA.INTEREST_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6959 ASFMA.INTEREST_Log Log of Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6960 ASFMA.INTEREST_mva200 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6961 ASFMA.INTEREST_mva050 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6962 ASFMA.INTEREST.by.GDP_YoY Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP Year over Year
6963 ASFMA.INTEREST.by.GDP_YoY4 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 4 Year over 4 Year
6964 ASFMA.INTEREST.by.GDP_YoY5 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 5 Year over 5 Year
6965 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6966 ASFMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6967 ASFMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6968 ASFMA.INTEREST.by.GDP_Log Log of Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6969 ASFMA.INTEREST.by.GDP_mva200 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 200 Day MA
6970 ASFMA.INTEREST.by.GDP_mva050 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
6971 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
6976 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6981 BOGMBASE.by.GDP_YoY4 BOGMBASE Divided by GDP 4 Year over 4 Year
6985 BOGMBASE.by.GDP_SmoothDer Derivative of Smoothed BOGMBASE Divided by GDP
6990 WALCL.by.GDP_YoY4 All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6991 WALCL.by.GDP_YoY5 All Federal Reserve Banks: Total Assets Divided by GDP 5 Year over 5 Year
6996 WALCL.by.GDP_mva200 All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6998 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
7003 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7012 DGS30TO10_SmoothDer Derivative of Smoothed Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7013 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7022 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7030 DGS10TO2_SmoothDer Derivative of Smoothed Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7031 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7037 DGS10TOTB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7039 DGS10TOTB3MS_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7040 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7041 DGS10TOTB3MS_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 200 Day MA
7042 DGS10TOTB3MS_mva050 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 50 Day MA
7048 DGS10TODTB3_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7049 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7050 DGS10TODTB3_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 200 Day MA
7066 LNU03000000BYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level (NSA) / Population
7070 UNEMPLOYBYPOPTHM_YoY Unemployment level, seasonally adjusted / Population Year over Year
7075 UNEMPLOYBYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level, seasonally adjusted / Population
7085 NPPTTLBYPOPTHM_Log Log of ADP Private Employment / Population
7086 NPPTTLBYPOPTHM_mva200 ADP Private Employment / Population 200 Day MA
7087 NPPTTLBYPOPTHM_mva050 ADP Private Employment / Population 50 Day MA
7088 U6toU3_YoY U6RATE minums UNRATE Year over Year
7089 U6toU3_YoY4 U6RATE minums UNRATE 4 Year over 4 Year
7091 U6toU3_Smooth Savitsky-Golay Smoothed (p=3, n=365) U6RATE minums UNRATE
7093 U6toU3_SmoothDer Derivative of Smoothed U6RATE minums UNRATE
7094 U6toU3_Log Log of U6RATE minums UNRATE
7096 U6toU3_mva050 U6RATE minums UNRATE 50 Day MA
7102 CHRISCMEHG1.by.PPIACO_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by commodities producer price index
7111 CHRISCMEHG1.by.CPIAUCSL_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by consumer price index
7118 DCOILBRENTEU.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7120 DCOILBRENTEU.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7122 DCOILBRENTEU.by.PPIACO_mva200 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
7123 DCOILBRENTEU.by.PPIACO_mva050 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 50 Day MA
7127 DCOILWTICO.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7129 DCOILWTICO.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7130 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7131 DCOILWTICO.by.PPIACO_mva200 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
7132 DCOILWTICO.by.PPIACO_mva050 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 50 Day MA
7156 LBMAGOLD.USD_PM.by.GDP_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
7172 GSG.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
7174 GSG.Close.by.GDPDEF_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7176 GSG.Close.by.GDPDEF_mva200 GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
7177 GSG.Close.by.GDPDEF_mva050 GSCI Commodity-Indexed Trust, Normalized by GDP def 50 Day MA
7178 GSG.Close.by.GSPC.Close_YoY GSCI Commodity-Indexed Trust, Normalized by S&P 500 Year over Year
7179 GSG.Close.by.GSPC.Close_YoY4 GSCI Commodity-Indexed Trust, Normalized by S&P 500 4 Year over 4 Year
7180 GSG.Close.by.GSPC.Close_YoY5 GSCI Commodity-Indexed Trust, Normalized by S&P 500 5 Year over 5 Year
7181 GSG.Close.by.GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7183 GSG.Close.by.GSPC.Close_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7184 GSG.Close.by.GSPC.Close_Log Log of GSCI Commodity-Indexed Trust, Normalized by S&P 500
7185 GSG.Close.by.GSPC.Close_mva200 GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
7186 GSG.Close.by.GSPC.Close_mva050 GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
7194 GDPBYPOPTHM_mva200 GDP/Population 200 Day MA
7238 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7239 GSPC.DailySwing_mva200 S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 200 Day MA
7262 HNFSUSNSA.minus.HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Houses for sale - houses sold
7264 HNFSUSNSA.minus.HSN1FNSA_SmoothDer Derivative of Smoothed Houses for sale - houses sold
7265 HNFSUSNSA.minus.HSN1FNSA_Log Log of Houses for sale - houses sold
7266 HNFSUSNSA.minus.HSN1FNSA_mva200 Houses for sale - houses sold 200 Day MA
7267 HNFSUSNSA.minus.HSN1FNSA_mva050 Houses for sale - houses sold 50 Day MA
7280 MSPUS.times.HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned 1-family units for sale times median price
7282 MSPUS.times.HNFSUSNSA_SmoothDer Derivative of Smoothed New privately owned 1-family units for sale times median price
7283 MSPUS.times.HNFSUSNSA_Log Log of New privately owned 1-family units for sale times median price
7284 MSPUS.times.HNFSUSNSA_mva200 New privately owned 1-family units for sale times median price 200 Day MA
7285 MSPUS.times.HNFSUSNSA_mva050 New privately owned 1-family units for sale times median price 50 Day MA
7312 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks. I updated this plot to include the estimated single-family home sales volume to give a sense of percentage of home sales that are cash.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 105 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 190 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 678 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.